UPFC based adaptive Neuro-Fuzzy Inference System controller for grid connected a DFIG wind farm

The objective of this paper is to design an Adaptive Neuro-Fuzzy Inference System (ANFIS) based controller for a Unified Power Flow Controller (UPFC) for improving the performance of Doubly Fed Induction Generator (DFIG) based wind farm to grid faults. The ANFIS based controller combines the advantages of a Fuzzy Logic Controller (FLC) as well as the quick response and adaptability nature of an artificial neural network. It is observed that the proposed UPFC controller reduces greatly fluctuations of the studied system after clearing fault. Further, the simulation results obtained are compared with conventional PI controller and PI-like FLC to show the effectiveness and robustness of the ANFIS based controller for UPFC.